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Record W2319635630 · doi:10.1061/40789(168)20

Pore Occlusion in Compacted Mixtures of Sand and Kaolinite Due to Bioclogging

2005· article· en· W2319635630 on OpenAlexaboutno aff
Sailaja Tumuluri, Lakshmi N. Reddi, George L. Marchin, Adam C. Henry

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsnot available
FundersUniversity of KansasNational Science Foundation
KeywordsKaoliniteDistilled waterHydraulic conductivityEffluentPorosityPermeationSoil waterNutrientMaterials scienceChemistryPorous mediumBiogasBacterial growthChemical engineeringPulp and paper industryEnvironmental scienceEnvironmental engineeringSoil scienceBacteriaMineralogyComposite materialWaste managementGeologyChromatographyMembrane

Abstract

fetched live from OpenAlex

Biokinetics in engineered soils is a subject of relatively recent interest. In this paper, results are presented from experimental studies to address the bioclogging mechanisms. The primary focus of this study is to assess the relative importance of biomass growth vs. biogas generated in the soil pores. Experiments were conducted using Pseudomonas aeruginosa as the bacterial culture and compacted mixtures of kaolinite and Ottawa sand as porous media. Results indicated about one order-of-magnitude reduction of permeabilities when the bacteria were introduced through a nutrient solution in the influent chamber. Compacted specimens prepared using a bacterial inoculum and permeated with nutrient solution alone showed that growth kinetics prevented the specimens from ever reaching the saturated hydraulic conductivities with respect to distilled deionized water. Bacterial counts in the influent and in the effluent revealed that the kinetic processes were similar in soil media and in the pure nutrient solution medium. Reductions in permeabilities were attributed to the biogas generated during bacteria permeation. Pore-size distributions of bioclogged specimens showed lager pores, which was also consistent with visual observations of specimen cracking and gas bubble accumulation at the surface of the specimens, particularly in the case of specimens prepared with bacteria inoculum.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.236
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2005
Admission routes1
Has abstractyes

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